The purpose of the proposed research is to increase the ease of independently navigating indoor spaces-in particular unfamiliar indoor spaces-for persons with a visual impairment. Currently this cannot be done without asking a sighted person for assistance. Further, the investigators want to determine the extent to which this might be done without installing a special building infrastructure (e.g., Talking Signs) and requiring persons to carry special technologies designed just for this purpose and only for this population. To this end the investigators wish to explore a new paradigm whereby building information databases would be implemented to meet the specific orientation and wayfinding needs of this population. These databases would assign geographic meaning to every detectable building feature, treating each detectable feature as a bread crumb that can be used to mark the route to a selected destination. In addition, this building database will contain information describing the accessibility of each building space so that the most accessible and easily traversed route to a selected destination can be plotted and followed. To test the feasibility of this new paradigm, there are three specific aims: (1) detectable types of building features will be defined and matched to the needs and diversity of this population, (2) a consistent and accurate means of capturing and organizing this building data will be developed using a robotic assistant, and (3) navigation performance of participants using this new system will be evaluated. To accomplish the First aim, 60 participants representing the diversity of the population will be recruited and asked to describe, across a variety of test settings, what features are detectable and meaningful to them. The resulting database will be organized according to naturally-occurring data groupings associated with participant skills and level of functional residual vision. A data presentation schema based on these data groupings will then be developed, so that the information provided each person matches their ability to use it effectively. For instance, visual cues would not be provided to persons with no light perception, and Braille-related information would not be provided to persons who do not read Braille. The second aim will be accomplished using a robot assistant that will be programmed to work as a semi-automated building surveyor assistant. This robot, developed at the Georgia Tech Healthcare Robotics Lab (HRL) as an assistant for persons with physical disabilities, was designed to be remotely driven through building spaces by a person with limited mobility. It employs a Light Detection and Ranging (LIDAR) system that produces 2D and 3D renderings of the spaces it is driven through and has a camera to capture images of the settings. Collected data will be processed and organized on a desktop computer by the surveyor. The third aim-evaluation of the building information system-will be accomplished employing 30 participants representing the diversity of the population. In counter-balanced cross-over trials participant performance using the developed database will be compared with performance where an Orientation and Mobility (O&M) instructor has fully trained the person how best to navigate that building environment. The hypotheses are as follows: {Hypothesis 1 - If building data of import to a visually impaired population for navigtion is customized to reduce the total amount of data to just that which is relevant to each person's actual needs (i.e., their level of skill, visual function, tactile function, etc.);then performance approaching that in a familiar route will result, where independent performance was previously unlikely to be successful.} {Hypothesis 2 - When the developed Georgia Tech HRL robot is used by an O&M expert to compile building data of import to a visually impaired population for navigation, the results (data collected) will be repeatable, reliable and consistent across a variety of building settings as indicated in test-retest trials.} PUBLIC HEALTH RELEVANCE: According to the VA website (http://commonspot.aao.org/veterans/news/low-vision.cfm), there are approximately 160,000 legally blind veterans. When you factor in the number of veterans diagnosed with low vision, the number jumps to more than one million. According to Tom Zampieri, director of government relations for the Blinded Veterans Association, "In 2007, there were 46,000 blinded veterans enrolled in the VA. Today, there are 49,000." The proposed research directly addresses the mission of the Department of Veterans Affairs by attending to "compensation for loss" issues and "quality of life" mandates. Difficulties orientating to and navigating through indoor spaces continue to be serious obstacles to independent travel for veterans with vision loss. Developing and deploying accessible building databases that provide this information will demonstrate respect for veterans by providing them with equal access to VA facilities, enhancing their functional independence, increasing their sense of self-reliance, self-respect, safety, and quality of life.